Taming Runaway Agents: OpenClaw 2026.2.17 Introduces Smart Tool Loop Detection

If you've ever watched your agent burn through tokens polling a process that will never finish, or cycling between the same two tool calls forever, OpenClaw 2026.2.17 has your back. The new progress-aware tool loop detection system (#16808) adds multiple layers of defense against stuck agents—and tells you exactly what's happening.

The Problem: Agents Get Stuck

AI agents are great at autonomously solving problems, but they're also capable of getting themselves into loops. Common patterns include:

• Poll loops: Repeatedly checking process(action=poll) or process(action=log) on a process that's stalled or waiting indefinitely
• Ping-pong patterns: Alternating between two calls that depend on each other but never make progress
• Retry storms: Making the same failing tool call over and over, hoping for a different result

Before 2026.2.17, these patterns could drain your token budget fast while producing nothing useful.

The Solution: Multi-Phase Detection

OpenClaw now watches for loop patterns across multiple levels:

1. Hard Blocks for Known No-Progress Patterns

Certain tool calls are now immediately blocked if they're clearly not making progress:

• Repeated process(action=poll) calls with no state change
• Repeated process(action=log) calls on the same session

These get caught early before tokens pile up.

2. Identical Call Warnings

When the agent makes the exact same tool call multiple times in succession, OpenClaw emits a warning. The agent can see this and (hopefully) try a different approach.

3. Ping-Pong Detection

This is clever: OpenClaw tracks alternating patterns. If the agent oscillates between two calls (A → B → A → B...) without progress, warnings escalate at 10 and 20 repetitions, eventually triggering intervention.

4. Global Circuit Breaker

If an agent makes 30 consecutive no-progress tool calls, the circuit breaker trips. This is your ultimate safety net—no more infinite loops burning through your API budget.

5. Structured Diagnostics

All loop events emit tool.loop diagnostic events (warning or error level), making it easy to monitor and alert on stuck agents in production.

What This Means for You

For most users: You don't need to do anything. These protections are on by default. If your agent was occasionally getting stuck, it'll now stop itself and tell you why.

For advanced users: Watch for tool.loop events in your logs. If you see them frequently, it's a signal to improve your agent's prompts or tool descriptions to help it recognize when to try a different approach.

For cost-conscious operators: This feature can significantly reduce wasted tokens from stuck runs. Combined with the existing timeout mechanisms, your agent budget is better protected.

The Technical Details

From the release notes:

Make loop detection progress-aware and phased by hard-blocking known process(action=poll|log) no-progress loops, warning on generic identical-call repeats, warning + no-progress-blocking ping-pong alternation loops (10/20), coalescing repeated warning spam into threshold buckets (including canonical ping-pong pairs), adding a global circuit breaker at 30 no-progress repeats, and emitting structured diagnostic tool.loop warning/error events for loop actions.

Thanks to @akramcodez and @beca-oc for contributing this feature!

Related Resources

• GitHub Issue #16808 - Original feature discussion
• OpenClaw v2026.2.17 Release Notes - Full changelog

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Have you encountered agent loops in production? Share your experiences in the comments—and let us know if this new detection system catches patterns we should know about.